Temporal and spatial variation of nitrogen transformations in nitrogen-saturated soils of a central Appalachian hardwood forest

We studied temporal and spatial patterns of soil nitrogen (N) dynamics from 1993 to 1995 in three watersheds of Fernow Experimental Forest, W.V.: WS7 (24-year-old, untreated); WS4 (mature, untreated); and WS3 (24-year-old, treated with (NH4)2SO since 1989 at the rate of 35 kg Nha–1year–1). Net nitrification was 141, 114, and115 kg Nha–1year–1, for WS3, WS4, and WS7, respectively, essentially 100% of net N mineralization for all watersheds. Temporal (seasonal) patterns of nitrification were significantly related to soil moisture and ambient temperaturein untreated watersheds only. Spatial patterns of soil water NO3–of WS4 suggest that microenvironmental variabilitylimits rates of N processing in some areas of this N-saturated watershed, in part by ericaceous species in the herbaceous layer. Spatial patterns of soil water NO3–in treated WS3 suggest that later stages of N saturation may result inhigher concentrations with less spatial variability. Spatial variability in soil N variables was lower in treated WS3 versus untreated watersheds. Nitrogen additions have altered the response of N-processing microbes to environmental factors, becoming less sensitive to seasonal changes in soil moisture and temperature. Biotic processes responsible forregulating N dynamics may be compromised in N-saturated forest ecosystems.

Factors Influencing Spatial Variability in Nitrogen Processing in Nitrogen-Saturated Soils

Nitrogen (N) saturation is an environmental concern for forests in the eastern U.S. Although several watersheds of the Fernow Experimental Forest (FEF), West Virginia exhibit symptoms of Nsaturation, many watersheds display a high degree of spatial variability in soil N processing. This study examined the effects of temperature on net N mineralization and nitrification in N-saturatedsoils from FEF, and how these effects varied between high N-processing vs. low N-processingsoils collected from two watersheds, WS3 (fertilized with [NH4]2SO4) and WS4 (untreated control). Samples of forest floor material (O2 horizon) and mineral soil (to a 5-cm depth) were taken from three subplots within each of four plots that represented the extremes of highest and lowest ratesof net N mineralization and nitrification (hereafter, high N and low N, respectively) of untreated WS4 and N-treated WS3: control/low N, control/high N, N-treated/low N, N-treated/high N. Forest floor material was analyzed for carbon (C), lignin,and N. Subsamples of mineral soil were extractedimmediately with 1 N KCl and analyzed for NH4+and NO3– to determine preincubation levels. Extracts were also analyzed for Mg, Ca, Al, and pH. To test the hypothesis that the lack of net nitrification observed in field incubations on the untreated/low N plot was the result of absence ofnitrifier populations, we characterized the bacterial community involved in N cycling by amplification of amoA genes. Remaining soil was incubated for 28 d at three temperatures (10, 20, and30°C), followed by 1 N KCl extraction and analysis for NH4+ and NO3–. Net nitrification was essentially 100% of net N mineralization for all samples combined. Nitrification rates from lab incubation sat all temperatures supported earlier observations based on field incubations. At 30°C, rates from N- t reated/high N were three times those of N-treated/low N. Highest rates were found for untreated/high N (two times greater than those of N-treated/high N), whereas untreated/low N exhibited no net nitrification. However, soils exhibitingno net nitrification tested positive for presence of nitrifying bacteria, causing us to reject our initial hypothesis. We hypothesize that nitrifier populations in such soil are being inhibited by a combination of low Ca:Al ratios in mineral soil and allelopathic interactions with mycorrhizae of ericaceous species in the herbaceous layer.

Effects of Silvicultural Practices on Soil Carbon and Nitrogen in a Nitrogen Saturated Central Appalachian (USA) Hardwood Forest Ecosystem

Silvicultural treatments represent disturbances to forest ecosystems often resulting in transient increases in net nitrification and leaching of nitrate and base cations from the soil. Response of soil carbon (C) is more complex, decreasing from enhanced soil respiration and increasing from enhanced postharvest inputs of detritus. Because nitrogen (N) saturation can have similar effects on cation mobility, timber harvesting in N-saturated forests may contribute to a decline in both soil C and base cation fertility, decreasing tree growth. Although studies have addressed effects of either forest harvesting or N saturation separately, few data exist on their combined effects. Our study examined the responses of soil C and N to several commercially used silvicultural treatments within the Fernow Experimental Forest, West Virginia, USA, a site with N-saturated soils. Soil analyses included soil organic matter (SOM), C, N, C/N ratios, pH, and net nitrification. We hypothesized the following gradient of disturbance intensity among silvicultural practices (from most to least intense): even-age with intensive harvesting (EA-I), even-age with extensive harvesting, even-age with commercial harvesting, diameter limit, and single-tree harvesting (ST). We anticipated that effects on soil C and N would be greatest for EA-I and least with ST. Tree species exhibited a response to the gradient of disturbance intensity, with early successional species more predominant in high-intensity treatments and late successional species more predominant in low-intensity treatments. Results for soil variables, however, generally did not support our predictions, with few significant differences among treatments and between treatments and their paired controls for any of the measured soil variables. Multiple regression indicated that the best predictors for net nitrification among samples were SOM (positive relationship) and pH (negative relationship). This finding confirms the challenge of sustainable management of N-saturated forests.

Effects of experimental freezing on soil nitrogen dynamics in soils from a net nitrification gradient in a nitrogen-saturated hardwood forest ecosystem

This study examined effects of soil freezing on N dynamics in soil along an N processing gradient within a mixed hardwood dominated watershed at Fernow Experimental Forest, West Virginia. Sites were designated as LN (low rates of N processing), ML (moderately low), MH (moderately high), and HN (high). Soils underwent three 7-day freezing treatments (0, –20, or –80 °C) in the laboratory. Responses varied between temperature treatments and along the gradient. Initial effects differed among freezing treatments for net N mineralization, but not nitrification, in soils across the gradient, generally maintained at LN < ML ≤ MH < HN for all treatments. Net N mineralization potential was higher following freezing at –20 and –80 °C than control; all were higher than at 0 °C. Net nitrification potential exhibited similar patterns. LN was an exception, with net nitrification low regardless of treatment. Freezing response of N mineralization differed greatly from that of nitrification, suggesting that soil freezing may decouple two processes of the soil N cycle that are otherwise tightly linked at our site. Results also suggest that soil freezing at temperatures commonly experienced at this site can further increase net nitrification in soils already exhibiting high nitrification from N saturation.

LIKELIHOOD ESTIMATION OF CONJUGACY RELATIONSHIPS IN LINEAR MODELS WITH APPLICATIONS TO HIGH-THROUGHPUT GENOMICS

In the simultaneous estimation of a large number of related quantities, multilevel models provide a formal mechanism for efficiently making use of the ensemble of information for deriving individual estimates. In this article we investigate the ability of the likelihood to identify the relationship between signal and noise in multilevel linear mixed models. Specifically, we consider the ability of the likelihood to diagnose conjugacy or independence between the signals and noises. Our work was motivated by the analysis of data from high-throughput experiments in genomics. The proposed model leads to a more flexible family. However, we further demonstrate that adequately capitalizing on the benefits of a well fitting fully-specified likelihood in the terms of gene ranking is difficult.

A HIDDEN MARKOV MODEL FOR JOINT ESTIMATION OF GENOTYPE AND COPY NUMBER IN HIGH-THROUGHPUT SNP CHIPS

Amplifications and deletions of chromosomal DNA, as well as copy-neutral loss of heterozygosity have been associated with diseases processes. High-throughput single nucleotide polymorphism (SNP) arrays are useful for making genome-wide estimates of copy number and genotype calls. Because neighboring SNPs in high throughput SNP arrays are likely to have dependent copy number and genotype due to the underlying haplotype structure and linkage disequilibrium, hidden Markov models (HMM) may be useful for improving genotype calls and copy number estimates that do not incorporate information from nearby SNPs. We improve previous approaches that utilize a HMM framework for inference in high throughput SNP arrays by integrating copy number, genotype calls, and the corresponding confidence scores when available. Using simulated data, we demonstrate how confidence scores control smoothing in a probabilistic framework. Software for fitting HMMs to SNP array data is available in the R package ICE.